Sales Forecasting 2024: How AI Is Making Forecasts More Accurate

Most sales organizations have a sales forecast accuracy of less than 75%. Even near the end of the quarter when accurate forecasts can make all the difference between an on-target quarter and poor performance, forecasts stay off track by at least 5%.

Poor forecasts hurt almost every part of the sales team—from the sales managers who choose goals and priorities to the sales reps who are striving for impossible goals to the clients who are hit with rushed and desperate pitches. But AI-powered sales forecasting is proving to be much more accurate than conventional models.

Promises about AI have been everywhere in the industry and in the news since long before generative AI splashed across the headlines. Diving into those promises one by one and understanding how AI structurally changes the sales forecasting process (and all the sales functions around those forecasts) will give your organization a better foundation for choosing AI tools that can fulfill those promises.

As your company progresses further along the AI revolution, take a close look at how AI is fundamentally addressing the conventional weaknesses of forecasts to improve both the forecasts themselves and your team’s ability to respond to them.

AI Is a Black Box, But You Don’t Have to Know What’s Going On Inside It to Know Where to Place It

For years, data and computer scientists have described complex ideas like AI and deep learning algorithms as “black boxes.” Inputs like data go in, and outputs like conclusions and data sets come out. The emergence of generative AI in popular business tools has not shed any light on what’s going on inside these black boxes, and as the algorithms get more specialized and sophisticated, we’ll know less and less.

Instead, experts measure the accuracy of the output and encourage algorithms to do more of whatever is resulting in those right answers . So AI tools are gaining more insight, and they’re becoming more accurate as time goes on. In addition, they’re understanding the patterns in and around the datasets they’re swallowing. 

Related: How Dell Technologies Improved Sales Rep Capabilities 24% with AI Role Play and Coaching

This means businesses can put those black boxes virtually anywhere in their processes. An AI black box positioned just after lead generation funnels can interpret the data and gauge which brand new leads are the most likely to be successful. You can position the black box further down the line at the opportunity level, and when you have an upcoming quarterly deadline, it can gauge which in-progress leads are the most likely to close. The possibilities are virtually endless.

• At the salesperson assignment stage: AI decides the best-fit salesperson.
• At the start of a renewal window: AI evaluates how likely clients are to stay.
• During onboarding: AI gauges which salespeople are most likely to stay long-term.
• During cold calls: AI can predict the messaging that works best.

So as your organization decides where to use AI and how to make the best use of it, it’s incredibly important to place it in the right spot in all of your processes for maximum success.

Zoom in on Sales Forecasting Where AI Is Making the Biggest Changes

Because sales forecasting is an incredibly important function in directing and managing your sales teams and because it’s uniquely about data and patterns, AI tools can really shine in giving your teams incredibly accurate forecasts on different timelines and for different areas of your business. Here are five places to position that black box.

Find New Connections and Trends in General Forecasting

Before you start exploring more complex use cases for AI-powered sales forecasting, it’s important to emphasize how much power you can unlock simply by feeding more data into the system. Remember, how AI works can be a little bit mysterious, and beyond a certain point, it’s impossible to know which small details are influential factors in your forecasts.

For example, hurricane season may mean that your southern East Coast clients are intermittently slow to respond. That’s seemingly impossible to explain to your CRM or ERP, but AI will pick up extended response times from past years and figure that into its projections.

At the beginning, start by simply giving your AI forecasting software all the clean, well-organized data you can. Then you can zoom into Q1 forecasts, Q2 renewal targets, reasonable quota goals, and so on. Once you have the right data ecosystem, you can run reports with the “questions”—or filters and time fields—for your current forecasting needs.

Now, you can dive into the more esoteric use cases.

Explore Hypotheticals to Find the Best Strategy for Your Organization

Sales forecasting tools are more dynamic than simply giving a view of a likely future—now they can give you a view of a likely future if. You can input information about potential changes like increasing your sales staff, focusing resources on a specific set of accounts, or changing the wording of cold calls. 

Depending on your software, you can set up specific experiments on hypothetical courses of action, or you can graph out the likely forecasts of multiple courses of action to choose the most appropriate strategy. This extra forecasting punch elevates the process from seeing a goal future to having recommended pathways to reaching targets.

Course Correct Your Forecasting Over Time

Forecasting is never a one-and-done process. Your sales operations or sales enablement teams might traditionally create forecasts at the start of the quarter, at midway points, and in the final two-week stretch. But AI forecasts can be living models that recalibrate in near real time based on inputs in the system.

Based on how many leads are coming in, how fast salespeople are moving towards their goals, and dozens of other factors, your forecasting tools can constantly correct themselves and become more accurate. Not only does this tackle the issue of reaching the end of the quarter with wildly inaccurate models, but it also means every subsequent quarter has mountains more data to make more accurate predictions.

Your models can instantly absorb an upswing in interest, falls in the market, and even spotty attendance due to a temporary flu bug, so you can either prepare for bumpy patches or cruise to record-setting quotas.

Generate More Specific Lead Categories and Lead Scoring

If you position that black box in the lead-scoring portion of your operations, you can immediately fine-tune your processes by removing guesswork and having a more definite understanding of cold, warm, and hot leads. AI can instantly evaluate whether a lead should be a priority based on the lead generation channel, the information it can learn about the lead’s organization, and a history of touchpoints with the prospect. 

Based on the information, your system can rank the lead’s priority (especially if you’re in the busy last few days of a quarter), assign it to the best-fit salesperson, and measure how much time it’ll take to convert them.

Make the Pareto Principle Do the Heavy Lifting in Your Organization

The Pareto Principle is simple—20% of the work generates 80% of the value. By zeroing in on the most valuable leads (either the ones that promise the most revenue or the ones that will require the fewest expenses), you can increase your profits. The trick has always been correctly identifying that 20%.

Related: How AI-Powered Sales Coaches Can Transform Training Programs

AI largely resolves that problem. It can get closer to making sure your salespeople spend more time on better-qualified leads and less time on unproductive work.

Use AI Training So Salespeople Are Ready for the Trends

So far, we’ve largely looked at what AI can do to help you manage forecasts, clients, and leads. But it’s just as important to flip the lens around and use AI to gain a new perspective on your sales team. With AI-powered training tools, your team can:

• Assess individual sales performance in incredibly granular detail to find areas for improvement.
• Create realistic role-playing scenarios for practice and drilling on new messaging, best practices, and individual product-selling strategies.
• Benefit from personalized learning tracks that improve their performance without wasting their time.

These AI tools can then align with your forecasting models. You’ll be able to forecast the win rates for individual salespeople and whole sales teams based on their past performance and rate of learning. You can identify the right salespeople for different types of clients. You can even use AI tools to see how productive individuals are likely to be in hypotheticals with different client types, learning tracks, and quotas.

Keep Your Team’s Actions and Effort Locked on Target With AI-Powered Sales Forecasting

AI tools are disrupting the sales industry, and it’s easy to be swept away in the confusion and not know how things are going to end. But AI-powered sales forecasting tools give you much more control. You can decide where and how to place them in your sales enablement, forecasting, and selling workflows to maximum effect. You can even use them to understand both prospect and sales rep trends. At Quantified, we offer AI tools that will help you beat your forecast through scalable sales training and comprehensive sales enablement. Reach out today to start making your predictions and business decisions more accurate.